code: def test_fc_stack(
      first_layer_input_size: Optional[int],
      layers: Optional[List],
      num_layers: Optional[int],
  ):
      set_random_seed(RANDOM_SEED)
      fc_stack = FCStack(
          first_layer_input_size=first_layer_input_size,
          layers=layers,
          num_layers=num_layers,
      ).to(DEVICE)
      input_tensor = torch.randn(
          BATCH_SIZE, first_layer_input_size, device=DEVICE
      )
      output_tensor = fc_stack(input_tensor)
      assert output_tensor.shape[1:] == fc_stack.output_shape
  
file_path: ludwig/tests/ludwig/modules/test_fully_connected_modules.py
imports: from typing import List, Optional
  import numpy
  import pytest
  import torch
  from ludwig.modules.fully_connected_modules import FCLayer, FCStack
  from ludwig.utils.misc_utils import set_random_seed
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 2 for calling a global function with example usage: test_fc_stack(first_layer_input_size, layers, num_layers) without return types